SRAM-Based Processing-in-Memory (PIM)

H Kim, C Yu, B Kim - Processing-in-Memory for AI: From Circuits to …, 2022 - Springer
SRAM-based PIM gained popularity from its implementation simplicity using active device-
only and compatibility with the standard CMOS logic process. Unlike the DRAM macro that is …

In-Memory Computing Using FLASH Memory

Y Halawani, B Mohammad - In-Memory Computing Hardware Accelerators …, 2023 - Springer
FLASH is a type of electrically erasable read-only memory (EEPROM), where the program
code is usually stored. It requires high programming voltages at the control gate in order to …

Compute-in-memory designs for deep neural network and combinatorial optimization problems accelerators

S Xie - 2023 - repositories.lib.utexas.edu
The unprecedented growth in Deep Neural Networks (DNN) model size has resulted into a
massive amount of data movement from off-chip memory to on-chip processing cores in …

[PDF][PDF] A Survey of SRAM-Based Processing-in-Memory Techniques and Applications

S Mittal, G Verma, B Kaushik, FA Khanday - researchgate.net
As von-Neumann computing architectures become increasingly constrained by data-
movement overheads, researchers have started exploring processing-in-memory (PIM) …

SRAM-Based In-Memory Computing: Circuits, Functions, and Applications

E Hassan, HT Tesfai, B Mohammad… - In-Memory Computing …, 2012 - Springer
As the demand for data-centric applications grows, traditional Von Neumann architectures
are increasingly strained. The frequent need for memory access in computing AI models and …

PIM for ML Training

J Heo, JY Kim - Processing-in-Memory for AI: From Circuits to Systems, 2012 - Springer
Abstract Machine learning (ML) inference is the evaluation process of a trained model for a
given input. To this end, it reads the input data and sends it through the various ML layers …